Improvement of Prediction of Noncontact Injury in Elite Australian Footballers With Repeated Exposure to Established High-Risk Workload Scenarios

Maximum speed exposures in Australian rules football: do methods matter?

This study compared weekly near-to-maximum speed exposure data when determined via different methods and criteria. Forty-seven professional Australian rules football (AF) players undertook pre-season sprint assessments (PSSA) via 3 × 50 m maximal efforts using 10 Hz GPS over two consecutive seasons. The same technology was used continually during the in-season to identify maximum speeds attained in training and matches. Weekly near-to-maximal speed (MS) exposure counts were aggregated for speeds ≥80%, ≥85%, ≥90% and ≥95% of their individual maximum for both determination approaches. Weekly near-to-MS exposures was lower (p < 0.0001) when determined from in-season monitoring for ≥80% (-1.26; CI: -1.58 to -0.93), ≥85% (-0.78; CI: -0.97 to -0.59), ≥90% (-0.42; CI: -0.53 to -0.32), and ≥95% (-0.09; CI: -0.12 to -0.06) versus PSSA, with no effect of playing position (P ≥ 0.161). Although ≥80% and ≥85% near-to-maximum speed exposure data was meaningfully influenced by the determination method, the effect was somewhat trivial at higher speed criteria (≥90% and ≥95%) often considered important for performance gains and injury risk reduction purposes. Maximum speed determination methods therefore may be used interchangeably, and discrete sprint assessments may not be necessary for this purpose.

In-Game Workload Demands of Position Players in Major League Baseball

BACKGROUND

Athletes who are well prepared for the physical demands of competition are less susceptible to injury. Defining and then preparing athletes for these in-game demands is critical to athlete health and performance. The injury burden within Major League Baseball (MLB) is significant and differs by position. Despite its importance, the workload demands have not been described for position players in MLB.

HYPOTHESIS

That running demands would be significantly higher for outfielders, followed by infielders, and catchers, respectively, while batting and baserunning metrics would be similar across positions.

STUDY DESIGN

Cohort study.

LEVEL OF EVIDENCE

Level 3.

METHODS

Total and high-speed running distance (>75% Vmax), high-speed running count, hard accelerations (>2.78 m/s/s), defensive and baserunning minutes, total and hard throws (>75% max), and bat swing counts were calculated from Statcast data. Players with 100 games or more in the 2018 season (n = 126) were included for analysis.

RESULTS

All offensive and baserunning metrics were similar across positions; however, significant positional differences were observed for defensive and overall workload metrics. High-speed running was highest among outfielders (F1,7 = 27.1, P < 0.01), followed by infielders, then catchers. Hard accelerations (F1,7 = 12.9, P < 0.01) were highest among first basemen, then outfielders, remaining infielders, and catchers. Total throws (F1,7 = 17.7, P < 0.01) were highest among middle infielders. Hard throws (P < 0.01) were highest among shortstops and third basemen.

CONCLUSION

In-game workloads differ significantly by defensive position in MLB. These differences in running, throwing, and hitting volumes have significant implications for physical preparation and injury return-to-play progressions to optimize performance and minimize injury and reinjury risk for these athletes.

CLINICAL RELEVANCE

These data provide insight into how best to prepare athletes of different positions for the demands of the game both in terms of preseason preparation as well as return-to-play benchmarks following injury. These data should also serve as a platform for future research into the relationship between workload and injury among professional baseball players.

Hamstring Strain Injury Prevention: Current Beliefs and Practices of Practitioners Working in Major League Baseball

CONTEXT

Hamstring strain injury (HSI) is the most frequently sustained injury in Major League Baseball (MLB). However, the beliefs and practices of practitioners working in MLB regarding HSI risk factors and prevention strategies in baseball athletes have not been documented.

OBJECTIVE

To document the current beliefs and practices of practitioners working in MLB regarding HSI prevention.

DESIGN

Cross-sectional study.

SETTING

Major League Baseball via an online survey.

PATIENTS OR OTHER PARTICIPANTS

Athletic trainers, physical therapists, and strength and conditioning coaches working in MLB during the 2021 season.

DATA COLLECTION AND ANALYSIS

An online survey was conducted, with participants completing the survey once. Questions pertained to risk factor identification, the use and perceived effectiveness of prevention strategies, and barriers to implementation. Descriptive statistics were calculated for each question.

RESULTS

A total of 91 responses were received featuring respondents from 28 of 30 MLB organizations. The perceived most important intrinsic risk factors were tolerance to high-speed running for first-time HSI and previous HSI for recurrent injury. The perceived most important extrinsic risk factor for both first-time and recurrent HSI was internal communication between staff. The perceived most effective prevention strategies were managing overall workload, regular exposure to high-speed running, and periodization. The most used prevention strategies were core or lumbopelvic strengthening, traditional resistance-training exercises, and managing overall workload. Approximately half (53%) of respondents reported barriers to effective implementation of HSI prevention strategies, including player and coach buy-in, compliance, workload management, and scheduling.

CONCLUSIONS

This was the first survey to investigate MLB practitioner beliefs and practices regarding HSI prevention. Responses from practitioners regarding their beliefs about risk factors and appropriate prevention strategies varied, and discrepancies existed between the perceived most effective strategies and those most frequently used.

Economic impact of muscle injury rate and hamstring strain injuries in professional football clubs. Evidence from LaLiga

The aims of this study were: 1) to describe the total muscular injuries, and specifically HSIs, and their corresponding missed matches; 2) to analyse their economic impact; and 3) to estimate the loss of incomes due to TV rights, in first division clubs from LaLigaTM depending on the expected and actual ranking position during the 2018/2019 season. To do that, a cross-sectional study for season 18/19 and for all players of the 20 Spanish professional football clubs was performed. The economic impact of injuries was estimated considering the missed matches and salary cost of all players and the audio-visual income loss was estimated considering the Spanish Royal Decree of Law (RDL 5/2015). The high number of muscular (270) and hamstring injuries (57) implies a high cost for professional first division football clubs, specifically € 365,811 per month for the former and € 47,388 per month for the latter. In addition, reaching a worse than expected position in LaLigaTM ranking involved a loss of 45,2 million € in TV rights incomes. The high cost of muscle injuries in first division teams justifies the need for multidisciplinary teams that are capable of reducing the number of injuries as well as recovery times.

If You Want to Prevent Hamstring Injuries in Soccer, Run Fast: A Narrative Review about Practical Considerations of Sprint Training

Hamstring strain injuries (HSIs) are one of the most common injuries in sprint-based sports. In soccer, the ability to sprint is key, not only because of its relation to performance but also due to its possible protective effect against HSIs. Although many authors have focused on the "how", "when", and "what" training load should be implemented, there is a lack of practical proposals for sprint training in a high-level professional environment. The objective of this narrative review is, after a deep review of the scientific literature, to present a practical approach for sprint training, trying to answer some of the questions that most strength and conditioning coaches ask themselves when including it in soccer. Once the literature published on this topic was reviewed and combined with the practical experience of the authors, it was concluded that sprint training in soccer, although it presents an obvious need, is not something about which there is methodological unanimity. However, following the practical recommendations from this narrative review, strength and conditioning coaches can have a reference model that serves as a starting point for optimal management of the internal and external training load when they wish to introduce sprint training in the competitive microcycle in professional soccer players, with the aim of reducing HSIs.

An Analysis of Positional Generic and Individualized Speed Thresholds Within the Most Demanding Phases of Match Play in the English Premier League

OBJECTIVES

To analyze the positional distances covered above generic and individualized speed thresholds within the most demanding phases of match play. Categorized by position, 17 English Premier League players' match data were analyzed over 2 consecutive seasons (2019-20 and 2020-21). The most demanding phases of play were determined using a rolling average across 4 periods of 1, 3, 5, and 10 minutes. Distance covered in the time above the standard speed of 5.5 m/s was analyzed, with individualized metrics based on the maximal aerobic speed (MAS) test data.

RESULTS

Central defenders displayed lower values for high-intensity periods when compared with fullbacks, midfielders, and wide midfielders for both generic and individualized metrics. MAS during 1-minute periods was significantly higher for forwards when compared with central defenders (82.9 [18.9] vs 67.5 [14.8] for maximum high-speed running [HSR] and 96.0 [15.9] vs 75.7 [13.8] HSR for maximum MAS activity). The maximum effect size differences between the central midfielders, wide midfielders, and fullbacks for HSR and MAS measures under the maximum HSR criterion was 0.28 and 0.18 for the 1-minute period, 0.36 and 0.19 for the 3-minute period, 0.46 and 0.31 for the 5-minute period, and 0.49 and 0.315 for the 10-minute period.

CONCLUSIONS

Individualized speed metrics may provide a more precise and comparable measure than generic values. Data appear to be consistent across playing positions except for central defenders. This information may allow practitioners to directly compare individualized physical outputs of non-central defenders during the most demanding phases of play regardless of the players' positional group. This may provide coaches with important information regarding session design, training load, and fatigue monitoring.

Reduced Match Exposure in the Previous 2 Matches Accounts for Hamstring Muscle Injury Incidence in Professional Football Players

BACKGROUND

Hamstring strain injuries are one of the most prevalent injuries in football (soccer). We examined the influence of accumulated match-play exposure on the occurrence of hamstring strain injury in professional football from 2 teams (Spanish 1st Division, LaLiga) over 3 seasons, and determined specific cut-off points as indicators of injury risk.

HYPOTHESIS

Overloaded players would be more likely to sustain a hamstring injury.

STUDY DESIGN

Prospective, controlled, observational study.

LEVEL OF EVIDENCE

Level 2b.

METHODS

Playing time, total running distance, and high-speed running (>24 km/h) distance during official matches of players that sustained a hamstring injury were compared with uninjured, paired controls. Cumulative playing time and running performance of 4 matches before the injury was computed. Relative risk (RR) of injury occurrence was estimated by generalized estimating equations. Diagnostic accuracy was determined by receiver operating characteristics and the area under the curve.

RESULTS

Thirty-seven hamstring strain injuries occurred, representing 23 ± 18 absence days per injury. Thirty-seven controls (uninjured players) were used as comparators. Low match-play exposures during 1 and 2 matches before injury were likely to explain injury occurrence (RR: 14-53%; P < 0.01). Metrics from the match before the hamstring muscle strain demonstrated the best accuracy to predict injury occurrence: high-speed running distance ≤328 m (sensitivity, 64%; specificity, 84%), playing time ≤64 min (sensitivity, 36%; specificity, 97%), and running distance ≤5.8 km (sensitivity, 39%; specificity, 97%).

CONCLUSION

Relatively reduced competitive exposure in the previous 2 matches was associated with higher hamstring injury risk in professional football players.

CLINICAL RELEVANCE

Screening simple metrics such as the accumulated match exposure during official matches and considering specific cut-off points for some running variables may be good indicators of injury risk and may assist in better individual injury management in professional soccer players.

The Trade Secret Taboo: Open Science Methods are Required to Improve Prediction Models in Sports Medicine and Performance

Clinical prediction models in sports medicine that utilize regression or machine learning techniques have become more widely published, used, and disseminated. However, these models are typically characterized by poor methodology and incomplete reporting, and an inadequate evaluation of performance, leading to unreliable predictions and weak clinical utility within their intended sport population. Before implementation in practice, models require a thorough evaluation. Strong replicable methods and transparency reporting allow practitioners and researchers to make independent judgments as to the model's validity, performance, clinical usefulness, and confidence it will do no harm. However, this is not reflected in the sports medicine literature. As shown in a recent systematic review of models for predicting sports injury models, most were typically characterized by poor methodology, incomplete reporting, and inadequate performance evaluation. Because of constraints imposed by data from individual teams, the development of accurate, reliable, and useful models is highly reliant on external validation. However, a barrier to collaboration is a desire to maintain a competitive advantage; a team's proprietary information is often perceived as high value, and so these 'trade secrets' are frequently guarded. These 'trade secrets' also apply to commercially available models, as developers are unwilling to share proprietary (and potentially profitable) development and validation information. In this Current Opinion, we: (1) argue that open science is essential for improving sport prediction models and (2) critically examine sport prediction models for open science practices.

Assessing the Relationship Between External Workloads and Noncontact Injuries During Summer Conditioning and Preseason Practice in National Collegiate Athletic Association Division 1 Football Players

ABSTRACT

Burghardt, WP, Pfeiffer, KA, and Kuenze, C. Assessing the relationship between external workloads and noncontact injuries during summer conditioning and preseason practice in National Collegiate Athletic Association Division 1 football players. J Strength Cond Res 37(4): 816-822, 2023-The purpose of this study was to prospectively investigate the relationship between noncontact injuries and workload in collegiate football during summer conditioning and preseason training. Workload and noncontact injury data were collected over the summer conditioning and preseason practice periods for a Division 1 National Collegiate Athletic Association football team ( n = 34). Seven- and 21-day exponentially weighted moving averages (EWMA) were calculated daily for each athlete. The acute:chronic ratio (A:C ratio) of these 2 measures was also calculated daily. Injury rates for noncontact injuries were calculated for both periods. Continuous variable modeling (panel logistic regression and restricted cubic spline) was used to assess the relationship of EWMA A:C ratio and noncontact injury using a 3-day lag period. Athletic exposures (AEs) were defined as individual sport training, practice, or competition sessions. Nine injuries were observed (6.97/1,000 AEs), with 4 injuries resulting in lost time (3.09/1,000 AEs). The mean EWMA A:C ratio was 0.92 ± 0.41 (95% confidence interval: 0.03-2.09). Both the panel logistic regression and the restricted cubic spline models showed a significant relationship between EWMA A:C ratio and noncontact injuries. However, the odds ratio (14.16) in the logistic regression had a very large standard error (14.51) and a wide 95% confidence interval (1.90-105.49). The restricted cubic spline model had a pseudo R2 of 0.136. Injury occurrence at given EWMA ratio values was lower than reported in previous research. Although both continuous models demonstrated a significant relationship between the EWMA A:C ratio and subsequent noncontact injuries over the next 3 days, neither model had sufficient goodness of fit to warrant adoption at this time.

From The Ground Up: Expert Perceptions of Lower Limb Activity Monitoring in Tennis

Understanding on-court movement in tennis allows for enhanced preparation strategies to improve player readiness and performance. Here, we explore expert physical preparation coaches' perceptions of elite training strategies for preparation and performance in tennis, with special reference to lower limb activity. Thirteen world renowned tennis strength and conditioning coaches were interviewed in a semi-structured method that explored four key topic areas of physical preparation for tennis: i) the physical demands; ii) load monitoring practice; iii) the direction of ground reaction forces application during match-play; and iv) the application of strength and conditioning for tennis. Three higher-order themes emerged from these discussions: i) off-court training for tennis should be specific to the demands of the sport, ii) the mechanical understanding of tennis lags our physiological approach, and iii) our understanding of the lower limb's contribution to tennis performance is limited. These findings provide valuable insights into the importance of improving our knowledge relevant to the mechanical demands of tennis movement, whilst highlighting important practical considerations from leading tennis conditioning experts.

Profiling the Typical Training Load of a Law Enforcement Recruit Class

Law enforcement academies, designed to prepare recruits for their prospective career, represent periods of high physical and mental stress, potentially contributing to recruits' injuries. Managing stress via monitoring training loads may mitigate injuries while ensuring adequate preparation. However, it is vital to first understand an academy's typical training load. The aim of this study was to profile the typical training load of law enforcement recruits over the course of 22 weeks. Data were prospectively collected using global positioning system (GPS) units placed on recruits during a portion of the academy training, while a desktop analysis was retrospectively applied to six other classes. A Bland-Altman plot was conducted to assess the agreement between the two methods. A linear mixed model was conducted to analyse the difference in distances covered per week, while other variables were presented graphically. Adequate agreement between the desktop analysis and GPS units was observed. Significant differences (p-value < 0.01) in distance covered (9.64 to 11.65 km) exist between weeks during early academy stages, which coincide with increases (~6 h) in physical training. Significant decreases in distances were experienced during the last five weeks of academy training. Most acute:chronic workload ratios stayed between the proposed 0.8 to 1.3 optimal range. Results from this study indicate that large increases in training occur early in the academy, potentially influencing injuries. Utilizing a desktop analysis is a pragmatic and reliable approach for instructors to measure load.

The Influence of Weekly Sprint Volume and Maximal Velocity Exposures on Eccentric Hamstring Strength in Professional Football Players

Background: Hamstring strains are the most common moderate-major severity injuries in football. The majority of hamstring injuries occur during sprinting, with low eccentric hamstring strength being associated with an elevated risk. Objective: To examine the relationship between sprinting and eccentric hamstring strength by monitoring total weekly sprint distance and weekly efforts > 90% and >95% of maximum velocity. Methods: Fifty-eight professional male footballers were observed over one-and-a-half seasons. Players’ running was monitored during training and matches using GPS, and eccentric hamstring strength was measured weekly. Results: Weekly sprint distance (ρ = −0.13, p < 0.01) and weekly efforts >90% of maximum velocity (ρ = −0.08, p = 0.01) both displayed significant inverse relationships with the percentage change in eccentric hamstring strength; weekly efforts >95% of maximum velocity showed no relationship with hamstring strength (ρ = −0.02, p = 0.45). Only weekly efforts >90% of maximum velocity significantly influenced the mean percentage change in eccentric hamstring force, F(3,58) = 3.71, p = 0.01, with significant differences occurring when comparing 7−8 sprint efforts with 0−2 efforts (0.11%, p = 0.03) and 5−6 efforts (0.12%, p = 0.03). Conclusions: Eccentric hamstring strength levels significantly decrease when 7−8 weekly sprint efforts are completed at >90% of maximum velocity. Monitoring weekly sprint loading at velocities > 90% of maximum velocity may be valuable to help to reduce the risk of hamstring injuries in professional football.

Just How Confident Can We Be in Predicting Sports Injuries? A Systematic Review of the Methodological Conduct and Performance of Existing Musculoskeletal Injury Prediction Models in Sport

BACKGROUND

An increasing number of musculoskeletal injury prediction models are being developed and implemented in sports medicine. Prediction model quality needs to be evaluated so clinicians can be informed of their potential usefulness.

OBJECTIVE

To evaluate the methodological conduct and completeness of reporting of musculoskeletal injury prediction models in sport.

METHODS

A systematic review was performed from inception to June 2021. Studies were included if they: (1) predicted sport injury; (2) used regression, machine learning, or deep learning models; (3) were written in English; (4) were peer reviewed.

RESULTS

Thirty studies (204 models) were included; 60% of studies utilized only regression methods, 13% only machine learning, and 27% both regression and machine learning approaches. All studies developed a prediction model and no studies externally validated a prediction model. Two percent of models (7% of studies) were low risk of bias and 98% of models (93% of studies) were high or unclear risk of bias. Three studies (10%) performed an a priori sample size calculation; 14 (47%) performed internal validation. Nineteen studies (63%) reported discrimination and two (7%) reported calibration. Four studies (13%) reported model equations for statistical predictions and no machine learning studies reported code or hyperparameters.

CONCLUSION

Existing sport musculoskeletal injury prediction models were poorly developed and have a high risk of bias. No models could be recommended for use in practice. The majority of models were developed with small sample sizes, had inadequate assessment of model performance, and were poorly reported. To create clinically useful sports musculoskeletal injury prediction models, considerable improvements in methodology and reporting are urgently required.

Associations between refined athlete monitoring measures and individual match performance in professional Australian football

The purpose of this study was to assess relationships between measures of training load, training response and neuromuscular performance and changes in individual match performance in professional Australian football. Data were collected from 45 professional Australian footballers from one club during the 2019 competition season. External load was measured by GPS technology. Internal load was measured via session rate of perceived exertion (sRPE). Perceptual wellness was measured via pre-training questionnaires (1-5 Likert scale rating of soreness, sleep, fatigue, stress and motivation). Percentage of maximum speed was calculated relative to individual maximum recorded during preseason testing. Rolling derivative training load measures (7-day and 28-day) were calculated. Principal Component Analysis (PCA) identified eight uncorrelated components. PCA factor loadings were used to calculate summed variable covariates and single variables were chosen from components based on practicality and statistical contribution. Associations between covariates and performance were determined via linear Generalised Estimating Equations. Performance was assessed via Player Ratings from a commercial statistics company. Seven-day total distance, IMA event count and sRPE load showed significant positive relationships with performance (18-23% increase in performance z-score). No other covariates displayed significant associations with performance. Individual relative increases in training load within the 7-day period prior to a match may be beneficial for enhancing individual performance.

A Narrative Review for a Machine Learning Application in Sports: An Example Based on Injury Forecasting in Soccer

In the last decade, the number of studies about machine learning algorithms applied to sports, e.g., injury forecasting and athlete performance prediction, have rapidly increased. Due to the number of works and experiments already present in the state-of-the-art regarding machine-learning techniques in sport science, the aim of this narrative review is to provide a guideline describing a correct approach for training, validating, and testing machine learning models to predict events in sports science. The main contribution of this narrative review is to highlight any possible strengths and limitations during all the stages of model development, i.e., training, validation, testing, and interpretation, in order to limit possible errors that could induce misleading results. In particular, this paper shows an example about injury forecaster that provides a description of all the features that could be used to predict injuries, all the possible pre-processing approaches for time series analysis, how to correctly split the dataset to train and test the predictive models, and the importance to explain the decision-making approach of the white and black box models.

The Interval Between Matches Significantly Influences Injury Risk in Field Hockey

Fixture congestion increases injury risk in football, but how it impacts other sports is unclear. The aim of this study was to identify associations between match density and injury incidence in field hockey players. Injury data from a prospective cohort study of professional and youth players was analysed in two ways. Inter-match intervals were clustered into<2424-hours, 3–7-days, and 13 + days, and injury rate ratios (IRR) were calculated to identify differences between clusters in match injuries. Separately, a Lasso-penalised Poisson regression model was used to determine the association between match load across the previous 24-hours, 3-days, 7-days and 14-days, and match and training injuries. Injury rates in matches within 24-hours of the previous match were mostly significantly higher when compared to matches after 3–7-days (IRRs: 3.78; 6.77, P = 0.003; 0.005). While a higher match exposure in the preceding 24-hour and 3-day periods was associated with higher combined match and training injury rates (β̂ = 0.0001; 0.0018), a higher match exposure in the previous 7-and 14-day periods was associated with a reduced injury rate (β̂ = –0.0001; –0.0005). Due to the increased injury risk in matches 3-days and especially 24-hours following the previous fixture, match distribution should be cautiously planned.

Lower-limb injury in elite Australian football: A narrative review of kinanthropometric and physical risk factors

OBJECTIVE

This review aims to provide a succinct and critical analysis of the current physical and mechanical demands of elite Australian football while examining lower-limb injury and the associated physical and kinanthropometric risk factors.

METHODS

MEDLINE, PubMed, Web of Science and SPORTSDiscus electronic databases were searched for studies that investigated the playing demands, injury trends, and physical and kinanthropometric injury risk factors of elite Australian football. Articles from similar team sports including soccer and rugby (union and league) were also included.

RESULTS

While the physical demands of elite AF have steadied over the past decade, injury rates continue to rise with more than two-thirds of all injuries affecting the lower-limbs. Body composition and musculoskeletal morphological assessments are regularly adopted in many sporting settings with current research suggesting high and low body mass are both associated with heightened injury risk. However, more extensive investigations are required to determine whether the proportions of muscle and fat are linked. Repeated assessment of musculoskeletal morphology may also provide further insight into stress fracture rates.

CONCLUSIONS

While kinanthropometric and physical attributes are highly valued within elite sporting environments, establishing a deeper connection with injury may provide practitioners with more insight into current injury trends.

Evolution of Physical Demands of Australian Football League Matches from 2005 to 2017: A Systematic Review and Meta-Regression

BACKGROUND

There is extensive research investigating the match demands of players in the Australian Football League (AFL).

OBJECTIVE

This systematic literature review and meta-regression sought to analyse the evolution of in-game demands in AFL matches from 2005 to 2017, focusing on the relationship between volume and intensity.

METHODS

A systematic search of Ovid MEDLINE, Embase, Emcare, Scopus, SPORTDiscus, and Cochrane Library databases was conducted. Included studies examined the physical demands of AFL matches utilising global positioning system (GPS) technology. Meta-regression analysed the shift in reported volume (total distance and total match time) and intensity (metres per minute [m.min^-1], sprint duration and acceleration) metrics for overall changes, across quarters and positional groups (forwards, nomadics and defenders) from 2005 to 2017 inclusive and for each year between 2005 and 2007, 2007 and 2010, 2010 and 2012, and 2012 and 2015/2017 breakpoints.

RESULTS

Distance (p = 0.094), m.min^-1 (p = 0.494), match time (p = 0.591), time over 18 km·h^-1 (p = 0.271), and number of accelerations greater than 4 km·h^-1 (p = 0.498) and 10 km·h^-1 (p = 0.335) in 1 s did not change from 2005 to 2017. From 2005 to 2007 volume decreased (- 6.10 min of match time; p = 0.010) and intensity increased (6.8 m.min^-1 increase; p = 0.023). Volume and intensity increased from 2007 to 2010, evidenced by increases in total distance (302 m; p = 0.039), time over 18 km·h^-1 (0.31 min; p = 0.005), and number of accelerations greater than 4 km·h^-1 (41.1; p = 0.004) and 10 km·h^-1 (3.6; p = 0.005) in 1 s. From 2010 to 2012, intensity decreased, evidenced by reductions in metres per minute (- 4.3; p = 0.022), time over 18 km·h^-1 (- 0.93 min; p < 0.001), and number of accelerations greater than 4 km·h^-1 (- 104.4; p < 0.001) and 10 km·h^-1 (- 8.3; p < 0.001) in 1 s, whilst volume stabilised with no changes in distance (p = 0.068) and match time (p = 0.443). From 2012 to 2015/2017 volume remained stable and intensity increased with time over 18 km·h^-1 (0.27 min; p = 0.008) and number of accelerations greater than 4 km·h^-1 (31.6; p = 0.016) in 1 s increasing.

CONCLUSIONS

Changes in volume and intensity of AFL match demands are defined by discrete periods from 2007 to 2010 and 2010 to 2012. The interaction of rule and interpretation changes and coaching strategies play a major role in these evolutionary changes. In turn, modified game styles impact player game demands, training, and selection priorities. Standardisation and uniformity of GPS data reporting is recommended due to inconsistencies in the literature.

Magnitude, Frequency, and Accumulation: Workload Among Injured and Uninjured Youth Basketball Players

Overuse injuries are common in basketball. Wearable technology enables the workload to be monitored in sport settings. However, workload-injury models lack a biological basis both in the metrics recorded and how workload is accumulated. We introduce a new metric for monitoring workload: weighted jump height, where each jump height is weighted to represent the expected effect of the jump magnitude on damage to the tendon. The objectives of this study were to use principal components analysis to identify distinct modes of variation in all workload metrics accumulated over 1, 2, 3, and 4 weeks and to examine differences among the modes of variation in workload metrics between participants before the injury and uninjured participants. Forty-nine youth basketball players participated in their typical basketball practices and games, and lower extremity injuries were classified as patellar or Achilles tendinopathy, other overuse, or acute. An inertial measurement unit recorded the number and height of all jumps, and session rating of perceived exertion was recorded. The previous 1-, 2-, 3-, and 4-week workloads of jump count, jump height, weighted jump height, and session rating of perceived exertion were summed for each participant-week. Principal components analysis explained the variance in the accumulated workload variables. Using the retained principal components, the difference between the workload of injured participants in the week before the injury and the mean workload of uninjured participants was described for patellar or Achilles tendinopathy, overuse lower extremity injury, and any lower extremity injury. Participants with patellar or Achilles tendinopathy and overuse lower extremity injuries had a low workload magnitude for all variables in the 1, 2, 3, and 4 weeks before injury compared with the weeks before no injury. Participants with overuse lower extremity injuries and any lower extremity injury had a high previous 1-week workload for all variables along with a low previous 3- and 4-week jump count, jump height, and weighted jump height before injury compared with the weeks before no injury. Weighted jump height represents the cumulative damage experienced by tissues due to repetitive loads. Injured youth basketball athletes had a low previous 3- and 4-week workloads coupled with a high previous 1-week workload.

Data Reduction Approaches to Athlete Monitoring in Professional Australian Football

PURPOSE

To apply data reduction methods to athlete-monitoring measures to address the issue of data overload for practitioners of professional Australian football teams.

METHODS

Data were collected from 45 professional Australian footballers from 1 club during the 2018 Australian Football League season. External load was measured in training and matches by 10-Hz OptimEye S5 and ClearSky T6 GPS units. Internal load was measured via the session rate of perceived exertion method. Perceptual wellness was measured via questionnaires completed before training sessions with players providing a rating (1-5 Likert scale) of muscle soreness, sleep quality, fatigue, stress, and motivation. Percentage of maximum speed was calculated relative to individual maximum velocity recorded during preseason testing. Derivative external training load measures (total daily, weekly, and monthly) were calculated. Principal-component analyses (PCAs) were conducted for Daily and Chronic measures, and components were identified via scree plot inspection (eigenvalue > 1). Components underwent orthogonal rotation with a factor loading redundancy threshold of 0.70.

RESULTS

The Daily PCA identified components representing external load, perceived wellness, and internal load. The Chronic PCA identified components representing 28-d speed exposure, 28-d external load, 7-d external load, and 28-d internal load. Perceived soreness did not meet the redundancy threshold.

CONCLUSIONS

Monitoring player exposure to maximum speed is more appropriate over chronic than short time frames to capture variations in between-matches training-cycle duration. Perceived soreness represents a distinct element of a player's perception of wellness. Summed-variable and single-variable approaches are novel methods of data reduction following PCA of athlete monitoring data.

Workload a-WEAR-ness: Monitoring Workload in Team Sports With Wearable Technology. A Scoping Review

OBJECTIVES

To (1) identify the wearable devices and associated metrics used to monitor workload and assess injury risk, (2) describe the situations in which workload was monitored using wearable technology (including sports, purpose of the analysis, location and duration of monitoring, and athlete characteristics), and (3) evaluate the quality of evidence that workload monitoring can inform injury prevention.

DESIGN

Scoping review.

LITERATURE SEARCH

We searched the CINAHL, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, Embase, HealthSTAR, MEDLINE, PsycINFO, SPORTDiscus, and Web of Science databases.

STUDY SELECTION CRITERIA

We included all studies that used wearable devices (eg, heart rate monitor, inertial measurement units, global positioning system) to monitor athlete workload in a team sport setting.

DATA SYNTHESIS

We provided visualizations that represented the workload metrics reported, sensors used, sports investigated, athlete characteristics, and the duration of monitoring.

RESULTS

The 407 included studies focused on team ball sports (67% soccer, rugby, or Australian football), male athletes (81% of studies), elite or professional level of competition (74% of studies), and young adults (69% of studies included athletes aged between 20 and 28 years). Thirty-six studies of 7 sports investigated the association between workload measured with wearable devices and injury.

CONCLUSION

Distance-based metrics derived from global positioning system units were common for monitoring workload and are frequently used to assess injury risk. Workload monitoring studies have focused on specific populations (eg, elite male soccer players in Europe and elite male rugby and Australian football players in Oceania). Different injury definitions and reported workload metrics and poor study quality impeded conclusions regarding the relationship between workload and injury. J Orthop Sports Phys Ther 2020;50(10):549-563. doi:10.2519/jospt.2020.9753.

How Has Workload Been Defined and How Many Workload-Related Exposures to Injury Are Included in Published Sports Injury Articles? A Scoping Review

OBJECTIVE

To describe how workload-related exposure variables have been defined in sports injury articles, and to identify the number of workload-related exposure variables included in comparative analyses.

DESIGN

Scoping review.

LITERATURE SEARCH

PubMed, SPORTDiscus, and Scopus were systematically searched on March 13, 2020. Two reviewers independently screened the retrieved literature and selected articles for inclusion.

STUDY SELECTION CRITERIA

Prospective cohort studies using workload-related variables as the primary exposure to sports injury were eligible for inclusion.

DATA SYNTHESIS

The type (eg, distance, balls bowled) and construct of workload-related exposure variables (eg, acute-chronic workload ratio) were extracted and summarized in frequency tables.

RESULTS

A total of 648 articles were identified, and 45 were eligible for inclusion. Workload definition differed greatly, as sports- and workload-related exposure variables could be, but were not limited to, distance, balls bowled, session rating of perceived exertion, accelerations, soreness, and sleep. Within and across articles, authors used different constructs for workload-related exposure variables. For example, distance was represented as total distance, distance per week, distance per 2 weeks, and acute-chronic workload ratio. The number of workload-related exposure variables included in comparative analyses ranged from 1 to 336.

CONCLUSION

Studies used different definitions of workload-related exposure variables. The number of workload-related exposure variables in a single study ranged from 1 to 336. J Orthop Sports Phys Ther 2020;50(10):538-548. doi:10.2519/jospt.2020.9766.

Profiling the Post-match Top-up Conditioning Practices of Professional Soccer Substitutes: An Analysis of Contextual Influences

Hills, SP, Barrett, S, Busby, M, Kilduff, LP, Barwood, MJ, Radcliffe, JN, Cooke, CB, and Russell, M. Profiling the post-match top-up conditioning practices of professional soccer substitutes: An analysis of contextual influences. J Strength Cond Res 34(10): 2805-2814, 2020-Soccer practitioners implement "top-up" conditioning sessions to compensate for substitutes' limited match-play exposure. Although perceived to be valuable for reducing injury risk and augmenting positive physical adaptations, little research has considered the demands of post-match top-up training. To quantify post-match top-up responses, 31 professional soccer players wore 10 Hz microelectromechanical systems after 37 matches whereby they were selected in the match-day squad as substitutes (184 observations; 6 ± 5 observations·player). Linear mixed models and effect sizes (ES) assessed the influence of contextual factors on 23 physical performance variables. Top-ups lasted 17.13 ± 7.44 minutes, eliciting total and high-speed distances of 1.7 ± 6.2 km and 0.4 ± 1.7 km, respectively. Each contextual factor (i.e., position, substitution timing, match location, result, time of day, stage of the season, and fixture density) influenced at least 4 of the dependent variables profiled (p ≤ 0.05). Top-up duration; total, moderate-speed, and low-speed distance; and the number of repeated high-intensity efforts were greater for unused vs. used substitutes (ES: 0.38-0.73, small to moderate). Relative to away matches, home top-ups elicited heightened total, low-speed, and high-speed distances, alongside more moderate-speed accelerations and decelerations, and repeated high-intensity efforts (ES: 0.25-0.89, small to moderate). Although absolute and relative running distances were generally the highest when the fixture density was low, the greatest acceleration and deceleration demands were observed during the most congested fixture periods. Late-season top-ups typically elicited lower absolute physical responses than early and mid-season sessions. These data provide important information for practitioners when considering the aims and design of substitute top-up conditioning sessions, particularly with reference to contextual influences.

Clinical utility of measuring the size of the lumbar multifidus and quadratus lumborum muscles in the Australian football league setting: A prospective cohort study

OBJECTIVES

Test the odds of factors previously associated with lower limb injury (decreased size of the multifidus (MF) and increased size of the quadratus lumborum (QL) muscle) in an independent sample of Australian Rules Football (ARF) players.

DESIGN

Prospective cohort study.

SETTING

Professional ARF.

PARTICIPANTS

Forty-three male ARF players.

MAIN OUTCOME MEASURES

Cross-sectional areas (CSAs) of MF and QL muscles measured from pre-season ultrasound images. Playing season injuries were recorded by club personnel. A multivariable logistic regression model was used to evaluate the usefulness of MF and QL muscle size for predicting playing season lower limb injuries.

RESULTS

Fifteen players (35%) sustained a playing season lower limb injury. The multivariable model indicated that the odds of sustaining a lower limb injury during the season was 2.38 (95% CI: 1.18, 5.00; P = 0.017) times less likely for a one cm² increase from the mean value in MF muscle CSA at the L5 vertebral level after adjusting for CSA of the QL, age and BMI. The main effect and interaction models positively predicted 75% of players that sustained a lower limb injury during the season (sensitivity 80%, specificity 85%).

CONCLUSION

Future studies could examine the efficacy, feasibility and adherence of 'at risk' players to a pre-season training program aimed at increasing MF muscle size and monitor playing season injuries.

Training Load and Its Role in Injury Prevention, Part 2: Conceptual and Methodologic Pitfalls

In part 2 of this clinical commentary, we highlight the conceptual and methodologic pitfalls evident in current training-load-injury research. These limitations make these studies unsuitable for determining how to use new metrics such as acute workload, chronic workload, and their ratio for reducing injury risk. The main overarching concerns are the lack of a conceptual framework and reference models that do not allow for appropriate interpretation of the results to define a causal structure. The lack of any conceptual framework also gives investigators too many degrees of freedom, which can dramatically increase the risk of false discoveries and confirmation bias by forcing the interpretation of results toward common beliefs and accepted training principles. Specifically, we underline methodologic concerns relating to (1) measure of exposures, (2) pitfalls of using ratios, (3) training-load measures, (4) time windows, (5) discretization and reference category, (6) injury definitions, (7) unclear analyses, (8) sample size and generalizability, (9) missing data, and (10) standards and quality of reporting. Given the pitfalls of previous studies, we need to return to our practices before this research influx began, when practitioners relied on traditional training principles (eg, overload progression) and adjusted training loads based on athletes' responses. Training-load measures cannot tell us whether the variations are increasing or decreasing the injury risk; we recommend that practitioners still rely on their expert knowledge and experience.

The Training-Performance Puzzle: How Can the Past Inform Future Training Directions?

Over the past 20 years, research on the training-load-injury relationship has grown exponentially. With the benefit of more data, our understanding of the training-performance puzzle has improved. What were we thinking 20 years ago, and how has our thinking changed over time? Although early investigators attributed overuse injuries to excessive training loads, it has become clear that rapid spikes in training load, above what an athlete is accustomed, explain (at least in part) a large proportion of injuries. In this respect, it appears that overuse injuries may arise from athletes being underprepared for the load they are about to perform. However, a question of interest to both athletic trainers (ATs) and researchers is why some athletes sustain injury at low training loads, while others can tolerate much greater training loads? A higher chronic training load and well-developed aerobic fitness and lower body strength appear to moderate the training-injury relationship and provide a protective effect against spikes in load. The training-performance puzzle is complex and dynamic-at any given time, multiple inputs to injury and performance exist. The challenge facing researchers is obtaining large enough longitudinal data sets to capture the time-varying nature of physiological and musculoskeletal capacities and training-load data to adequately inform injury-prevention efforts. The training-performance puzzle can be solved, but it will take collaboration between researchers and clinicians as well as an understanding that efficacy (ie, how training load affects performance and injury in an idealized or controlled setting) does not equate to effectiveness (ie, how training load affects performance and injury in the real-world setting, where many variables cannot be controlled).

Global Positioning System-Derived Workload Metrics and Injury Risk in Team-Based Field Sports: A Systematic Review

OBJECTIVE

To evaluate the current literature regarding the utility of global positioning system (GPS)-derived workload metrics in determining musculoskeletal injury risk in team-based field-sport athletes.

DATA SOURCES

PubMed entries from January 2009 through May 2019 were searched using terms related to GPS, player workload, injury risk, and team-based field sports.

STUDY SELECTION

Only studies that used GPS metrics and had injury as the main outcome variable were included.

DATA EXTRACTION

Total distance, high-speed running, and acute : chronic workload ratios were the most common GPS metrics analyzed, with the most frequent sports being soccer, rugby, and Australian rules football.

DATA SYNTHESIS

Many distinct workload metrics were associated with increased injury risk in individual studies performed in particular sport circumstances; however, the body of evidence was inconclusive as to whether any specific metrics could consistently predict injury risk across multiple team-based field sports.

CONCLUSIONS

Our results were inconclusive in determining if any GPS-derived workload metrics were associated with an increased injury risk. This conclusion is due to a myriad of factors, including differences in injury definitions, workload metrics, and statistical analyses across individual studies.

The Relationship Between Acute: Chronic Workload Ratios and Injury Risk in Sports: A Systematic Review

PURPOSE

Low injury rates have previously been correlated with sporting team success, highlighting the importance of injury prevention programs. Recent methods, such as acute:chronic workload ratios (ACWR) have been developed in an attempt to predict and manage injury risk; however, the relation between these methods and injury risk is unclear. The aim of this systematic review was to identify and synthesize the key findings of studies that have investigated the relationship between ACWR and injury risk.

METHODS

Included studies were critically appraised using the Downs and Black checklist, and a level of evidence was determined. Relevant data were extracted, tabulated, and synthesized.

RESULTS

Twenty-seven studies were included for review and ranged in percentage quality scores from 48.2% to 64.3%. Almost perfect interrater agreement (κ = 0.885) existed between raters. This review found a high variability between studies with different variables studied (total distance versus high speed running), as well as differences between ratios analyzed (1.50-1.80 versus ≥1.50), and reference groups (a reference group of 0.80-1.20 versus ≤0.85).

CONCLUSION

Considering the high variability, it appears that utilizing ACWR for external (eg, total distance) and internal (eg, heart rate) loads may be related to injury risk. Calculating ACWR using exponentially weighted moving averages may potentially result in a more sensitive measure. There also appears to be a trend towards the ratios of 0.80-1.30 demonstrating the lowest risk of injury. However, there may be issues with the ACWR method that must be addressed before it is confidently used to mitigate injury risk. Utilizing standardized approaches will allow for more objective conclusions to be drawn across multiple populations.

Practitioner perceptions regarding the practices of soccer substitutes

Despite empirical observations suggesting that practitioners value the use of substitutions during soccer match-play, limited research has sought to substantiate such claims. This study used online surveys to assess the perceptions of practitioners within professional soccer about the use and practices of substitutes. Thirty-three practitioners completed one of two surveys (each requiring both open and closed questions to be answered), depending upon whether their primary role related mostly to tactical (‘tactical practitioners’; n = 7) or physical (‘physical practitioners’; n = 26) aspects of player/team management. Thematic content analysis of responses identified four higher-order themes: ‘impact of substitutions’, ‘planning and communication’, ‘player preparation and recovery’ and ‘regulations’. Eighty-five percent of practitioners believed that substitutes are important in determining success during soccer match-play, with the primary justification being the perceived ability of such players to provide a physical and/or tactical impact. However, contextual factors such as the match situation, timing of introduction, and players undergoing adequate pre-pitch-entry preparation, may be important for realising such aims. Although many practitioners believed that there was a need for substitutes to engage in bespoke non-match-day preparations and recovery strategies that differ from starting players, logistical considerations, such as scarcity of resources, often limit their scope. Notwithstanding, 96% of respondents indicated that substitutes frequently perform extra conditioning sessions to account for deficits in high-speed running loads compared with players exposed to a longer period of match-play. Substitutes’ pre-match warm-ups are typically led by team staff, however practitioners reported providing varying levels of input with regards to the practices adopted between kick-off and pitch-entry. Uncertainty exists as to the efficacy of current pre-pitch-entry practices, and 100% of practitioners highlighted ‘preparatory strategies’ as at least a ‘moderately important’ direction for future research. This study presents novel insights and highlights areas that are considered future research priorities amongst those working in the field.

Greater Association of Relative Thresholds Than Absolute Thresholds With Noncontact Lower-Body Injury in Professional Australian Rules Footballers: Implications for Sprint Monitoring

Sprint capacity is an important attribute for team-sport athletes, yet the most appropriate method to analyze it is unclear.

PURPOSE

To examine the relationship between sprint workloads using relative versus absolute thresholds and lower-body soft-tissue and bone-stress injury incidence in professional Australian rules football.

METHODS

Fifty-three professional Australian rules football athletes' noncontact soft-tissue and bone-stress lower-body injuries (N = 62) were recorded, and sprint workloads were quantified over ∼18 months using the global positioning system. Sprint volume (m) and exposures (n) were determined using 2 methods: absolute (>24.9 km·h-1) and relative (≥75%, ≥80%, ≥85%, ≥90%, ≥95% of maximal velocity). Relationships between threshold methods and injury incidence were assessed using logistic generalized additive models. Incidence rate ratios and model performances' area under the curve were reported.

RESULTS

Mean (SD) maximal velocity for the group was 31.5 (1.4), range 28.6 to 34.9 km·h-1. In comparing relative and absolute thresholds, 75% maximal velocity equated to ~1.5 km·h-1 below the absolute speed threshold, while 80% and 85% maximal velocity were 0.1 and 1.7 km·h-1 above the absolute speed threshold, respectively. Model area under the curve ranged from 0.48 to 0.61. Very low and very high cumulative sprint loads ≥80% across a 4-week period, when measured relatively, resulted in higher incidence rate ratios (2.54-3.29), than absolute thresholds (1.18-1.58).

DISCUSSION

Monitoring sprinting volume relative to an athlete's maximal velocity should be incorporated into athlete monitoring systems. Specifically, quantifying the distance covered at >80% maximal velocity will ensure greater accuracy in determining sprint workloads and associated injury risk.

Session Availability as a Result of Prior Injury Impacts the Risk of Subsequent Non-contact Lower Limb Injury in Elite Male Australian Footballers

Prior injury is a commonly identified risk factor for subsequent injury. However, a binary approach to classifying prior injury (i.e., yes/no) is commonly implemented and may constrain scientific findings, as it is possible that variations in the amount of time lost due to an injury will impact subsequent injury risk to differing degrees. Accordingly, this study investigated whether session availability, a surrogate marker of prior injury, influenced the risk of subsequent non-contact lower limb injury in Australian footballers. Data were collected from 62 male elite Australian footballers throughout the 2015, 2016, and 2017 Australian Football League seasons. Each athlete's participation status (i.e., full or missed/modified) and any injuries that occurred during training sessions/matches were recorded. As the focus of the current study was prior injury, any training sessions/matches that were missed due to reasons other than an injury (e.g., load management, illness and personal reasons) were removed from the data prior to all analyses. For every Monday during the in-season periods, session availability (%) in the prior 7, 14, 21, 28, 35, 42, 49, 56, 63, 70, 77, and 84 days was determined as the number of training sessions/matches fully completed (injury free) relative to the number of training sessions/matches possible in each window. Each variable was modeled using logistic regression to determine its impact on subsequent injury risk. Throughout the study period, 173 non-contact lower limb injuries that resulted in at least one missed/modified training session or match during the in-season periods occurred. Greater availability in the prior 7 days increased injury probabilities by up to 4.4%. The impact of session availability on subsequent injury risk diminished with expanding windows (i.e., availability in the prior 14 days through to the prior 84 days). Lesser availability in the prior 84 days increased injury probabilities by up to 14.1%, only when coupled with greater availability in the prior 7 days. Session availability may provide an informative marker of the impact of prior injury on subsequent injury risk and can be used by coaches and clinicians to guide the progression of training, particularly for athletes that are returning from long periods of injury.